Independent and Dependent Events Probability Independent and Dependent Events

Independent Events A occurring does NOT affect the probability of B occurring. “AND” means to MULTIPLY!

Independent Event FORMULA P(A and B) = P(A)  P(B) also known as P(A  B) = P(A)  P(B)

P(A  B) = P(A)  P(B) Example 1 A coin is tossed and a 6-sided die is rolled. Find the probability of landing on the head side of the coin and rolling a 3 on the die. P(Head and 3) P(A  B) = P(A)  P(B)

P(A  B) = P(A)  P(B) Example 2 A card is chosen at random from a deck of 52 cards. It is then replaced and a second card is chosen. What is the probability of choosing a jack and an eight? P(Jack and 8) P(A  B) = P(A)  P(B)

P(A  B) = P(A)  P(B) Example 3 A jar contains 3 red, 5 green, 2 blue and 6 yellow marbles. A marble is chosen at random from the jar. After replacing it, a second marble is chosen. What is the probability of choosing a green and a yellow marble? P(Green and Yellow) P(A  B) = P(A)  P(B)

Example 4 A school survey found that 9 out of 10 students like pizza. If three students are chosen at random with replacement, what is the probability that all three students like pizza? P(Like and Like and Like)

Mutually Exclusive vs. Independent ME events cannot happen at the same time. Venn diagram does not overlap. Ex: when tossing a coin, the result can either be heads or tails but not both. Independent events are the occurrence of one event is unaffected by other events. Ex: a coin is tossed twice, tail in the first chance and tail in the second. Venn diagram overlaps.

Mutually Exclusive vs. Independent P(A and B) = 0 The happening of one event makes the happening of another event impossible. (disjoint events) Independent: P(A and B) = P(A)*P(B) The happening of an event has no effect on the happening of another event.

Dependent Events A occurring AFFECTS the probability of B occurring Usually you will see the words “without replacing” “AND” still means to MULTIPLY!

Dependent Event Formula P(A and B) = P(A)  P(B given A) also known as P(A  B) = P(A)  P(B|A)

P(A  B) = P(A)  P(B|A) Example 5 A jar contains 3 red, 5 green, 2 blue and 6 yellow marbles. A marble is chosen at random from the jar. A second marble is chosen without replacing the first one. What is the probability of choosing a green and a yellow marble? P(Green and Yellow) P(A  B) = P(A)  P(B|A)

P(A  B) = P(A)  P(B|A) Example 6 An aquarium contains 6 male goldfish and 4 female goldfish. You randomly select a fish from the tank, do not replace it, and then randomly select a second fish. What is the probability that both fish are male? P(Male and Male) P(A  B) = P(A)  P(B|A)

P(A  B) = P(A)  P(B|A) Example 7 A random sample of parts coming off a machine is done by an inspector. He found that 5 out of 100 parts are bad on average. If he were to do a new sample, what is the probability that he picks a bad part and then, picks another bad part if he doesn’t replace the first? P(Bad and Bad) P(A  B) = P(A)  P(B|A)

Determining if 2 Events are Independent

Determining if Events are Independent 3 Ways to check. We are going to practice one of the ways: P(A  B) = P(A)  P(B) Substitute in what you know and check to see if left side equals right side.

Example 8 Let event M  = taking a math class. Let event S = taking a science class. Then, M and S = taking a math class and a science class. Suppose P(M) = 0.6, P(S) = 0.5, and P(M and S) = 0.3. Are M and S independent? Conclusion: Taking a math class and taking a science class are independent of each other.

Example 9 In a particular college class, 60% of the students are female. 50% of all students in the class have long hair. 45% of the students are female and have long hair. Of the female students, 75% have long hair. Let F be the event that the student is female. Let L be the event that the student has long hair. One student is picked randomly. Are the events of being female and having long hair independent? Conclusion: Being a female and having long hair are not independent.